Job Description
Architect the Future of Intelligence
Are you ready to define the technological landscape of 2026? Nexus Future Labs is seeking a visionary Senior AI Architect to lead our R&D efforts in Generative AI and Autonomous Systems. We are not just building software; we are engineering the cognitive infrastructure for the next decade.
In this pivotal role, you will bridge the gap between theoretical breakthroughs and scalable production systems. You will work alongside elite engineers and researchers to deploy next-generation Large Language Models (LLMs) and reinforcement learning agents that will redefine human-machine interaction.
Why Join Us?
- Work on cutting-edge projects that will shape the industry in 2026 and beyond.
- Competitive equity package and top-tier benefits.
- Flexible remote-first culture with a hub in the heart of SF.
What You Will Do:
Responsibilities
- Design and implement scalable, fault-tolerant AI infrastructure capable of handling petabyte-scale data streams.
- Lead the research and development of proprietary Large Language Models, focusing on efficiency and hallucination reduction.
- Collaborate with cross-functional teams to integrate AI capabilities into consumer and enterprise products.
- Establish best practices for model training, evaluation, and deployment using MLOps pipelines.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning and innovation.
- Stay ahead of the curve on emerging AI paradigms, including Neuromorphic Computing and Quantum Machine Learning.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Mathematics, or a related field, with a focus on Artificial Intelligence.
- Minimum of 7+ years of experience in software engineering and machine learning architecture.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of deploying production-grade AI models at scale.
- Strong understanding of distributed systems, cloud architecture (AWS/Azure/GCP), and containerization (Docker/K8s).
- Experience with LangChain, vector databases, and prompt engineering methodologies.